Analysis of differential metabolites in lung cancer patients based on metabolomics and bioinformatics.

Abstract

Aim: Based on metabonomics, the metabolic markers of lung cancer patients were analyzed, combined with bioinformatics to explore the underlying disease mechanism. Materials & methods: Based on case-control design, using UPLC-Q-TOF/MS, urine metabolites were detected in discovery and validation set. Multivariate statistical analysis were performed to identify potential markers for lung cancer. A network analysis was constructed to integrate lung cancer disease targets with the above metabolic markers, and its possible mechanism and biological significance were explained. Results: A total of 35 potential markers were identified, 11 of which overlapped. Five key markers have a good linear correlation with serum biochemical indicators. Conclusion: The occurrence and development of lung cancer are closely related to disturbance of D-Glutamine and D-glutamate metabolism, amino acid imbalance. This test was registered on China clinical trial registration center (www.chictr.org.cn/index.aspx), registration number was ChiCTR1900025543.

• Authors: Chenchen Zhao, Xianbin Kong, Shuang Han, Xiaojiang Li, Tong Wu, Jie Zhou, Yuzhu Guo, Zhichao Bu, Chuanxin Liu, Chenning Zhang, Yingjie Jia
• Journal: Future oncology (London, England) (Future Oncol) Vol. 16 Issue 18 Pg. 1269-1287 (Jun 2020) ISSN: 1744-8301 [Electronic] England
• PMID: 32356461 (Publication Type: Journal Article)

Chemical References

• Biomarkers

Topics

• Aged
• Biomarkers
• Case-Control Studies
• Chromatography, High Pressure Liquid
• Computational Biology (methods)
• Databases, Factual
• Energy Metabolism
• Female
• Humans
• Lung Neoplasms (blood, metabolism, urine)
• Male
• Metabolome
• Metabolomics (methods)
• Middle Aged
• ROC Curve
• Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization